PROJECT SUMMARY Kidney cancer (renal cell carcinoma, RCC) is now the 6th and 10th most common cancer diagnosed in men and women, respectively. Median overall survival for patients with metastatic RCC (mRCC) has improved in the targeted therapy era, but remains modest at 14 months. Immune checkpoint inhibitors (ICI) showed exceptional promise in early clinical trials for mRCC ? eventually leading to FDA approval of nivolumab (anti-PD-1) as a second-line treatment in 2016. In 2018, combination therapy with nivolumab plus ipilimumab (anti-cytotoxic T- lymphocyte-associated antigen 4; CTLA-4) demonstrated significant response rates in intermediate- and poor- risk RCC patients and has recently been approved as a first-line mRCC treatment. However, it is still unclear why immune checkpoint inhibitor (ICI) therapies are effective ? and remarkably so ? in only ~25% of patients with mRCC. There is also increasing awareness of the potential toxicities, and specifically the immune-related adverse events (irAEs), associated with checkpoint inhibitors. Therefore, there is an urgent need to identify mechanistic biomarkers that 1) reliably predict the development of irAEs, and 2) predict the response of mRCC to checkpoint inhibitors. In response to PQ8, our goal is to evaluate whether changes in intracellular signaling responses in peripheral blood immune cells taken before treatment from patients with mRCC could serve as ?predictive biomarkers for the onset of immune-related adverse events (irAEs) associated with checkpoint inhibition?. Our group, along with others, has shown that intracellular signaling responses in peripheral blood immune cells are correlated with response to chemotherapy in acute lymphoblastic leukemia (ALL), recovery from hip surgery, and full-term pregnancy. Furthermore, it was recently shown that a patient?s baseline immune state before i) surgery for hip replacement ii) chemotherapy for ALL iii) ICI treatment for metastatic melanoma were determinants of recovery, relapse and progression-free survival respectively. Our proposal is therefore built on the hypothesis that patients with mRCC receiving ICIs differ in their pre-drug immune state which will affect the onset of irAEs and clinical response. To address this, we will perform CyTOF analysis using peripheral blood measuring both cell abundance and intracellular signaling from 60 patients with mRCC before ICI administration. In Aim 1, based on our experience in streamlining the translation of CyTOF to clinical samples, we will use novel agents to standardize whole blood processing enabling the use of CyTOF ?at the bedside? to study the immune state pre-treatment with ICIs. In Aim 2, we will adapt multivariate regression algorithms to identify immune correlates for predicting irAEs and clinical response. Novel applications of these powerful statistical methods to mass cytometry datasets will ultimately form the analytical groundwork to examine the relationship between patient-specific immune traits before administration of, irAEs, and treatment efficacy.